The ad says“Cloud data warehouse or lakehouse platforms such as Amazon Redshift or Databricks”
The ad says“Workflow orchestration tooling such as Apache Airflow or Dagster”
The ad says“AWS data stack, including Glue and Spark”
The ad says“7+ years of professional experience in data engineering, infrastructure engineering, or backend software engineering”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“Workflow orchestration tooling such as Apache Airflow or Dagster”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“7+ years of professional experience in data engineering, infrastructure engineering, or backend software engineering”
The ad says“Fluent SQL and strong data-modeling skills, including designing schemas for a warehouse your team owns”
The ad says“Cloud data warehouse or lakehouse platforms such as Amazon Redshift or Databricks”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“7+ years of professional experience in data engineering, infrastructure engineering, or backend software engineering”
The ad says“Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability”
The ad says“SQL and Python”
The ad says“Strong software engineering craft: clean, correct, maintainable code with solid data-structure and problem-solving fundamentals”
The ad says“AWS data stack, including Glue and Spark”
The ad says“Fluent SQL and strong data-modeling skills, including designing schemas for a warehouse your team owns”
The ad says“Tableau or a comparable BI platform”
We are seeking a Senior or Staff Data Engineer to design, build, and own the data platform underneath our business-critical pipelines
Today the team supports account provisioning, product analytics, and the pipelines feeding our warehouse and Tableau reporting. You will help expand this into a globally deployed data platform spanning the warehouse, orchestration, and BI across multiple regions
Design, build, and maintain business-critical data pipelines, including data ingestion and AWS Glue/Spark jobs feeding the warehouse and Tableau
Build and operate core data infrastructure: the data warehouse, orchestration, and BI/reporting platform, deployed across multiple regions
Help evaluate and shape our warehouse strategy, including lakehouse platforms such as Databricks
Define and evolve event-driven contracts between producer and consumer teams, reasoning through batch vs. streaming, CDC, reprocessing, and multi-tenant/multi-region trade-offs
Design and evolve warehouse schemas and data models
Build observability into pipelines and platform components
Drive work across producer and consumer teams, communicate clearly, and own outcomes end to end
Benefits
Growth Opportunities: Be part of a dynamic and growing team with numerous career advancement opportunities
Innovation-Driven Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking
Inclusive and Diverse Team: We value diversity and promote an inclusive culture where everyone can thrive
Flexible Work Environment: Enjoy the convenience and work-life balance that comes with remote work
Preferred experience
Experience owning production data infrastructure end to end
Strong collaboration and ownership across dependent teams
7+ years of professional experience in data engineering, infrastructure engineering, or backend software engineering
Strong software engineering craft: clean, correct, maintainable code with solid data-structure and problem-solving fundamentals
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience
Fluent SQL and strong data-modeling skills, including designing schemas for a warehouse your team owns
Deep understanding of distributed systems and data architecture: pipeline and platform design, batch vs. streaming, CDC, event contracts, multi-tenant and multi-region trade-offs, reprocessing, and observability
Tableau or a comparable BI platform
Workflow orchestration tooling such as Apache Airflow, Dagster or similar
Experience with cloud-based data platforms and distributed data processing (e.g., AWS Glue, Databricks, Snowflake, or Spark-based pipelines)
